The dynamic development of computer and software technology in recent years was accompanied by the expansion and widespread implementation of artificial intelligence (AI) based methods in many aspects of human life. A prominent field where rapid progress was observed are high‐throughput methods in biology that generate big amounts of data that need to be processed and analyzed. Therefore, AI methods are more and more applied in the biomedical field, among others for RNA‐protein binding sites prediction, DNA sequence function prediction, protein‐protein interaction prediction, or biomedical image classification. Stem cells are widely used in biomedical research, e.g., leukemia or other disease studies. Our proposed approach of

Abstract: non-alcoholic fatty liver disease (NAFLD) is one of the widespread chronic liver diseases; it is ranging from simple fat buildup in the liver (steatosis) to non-alcoholic steatohepatitis (NASH) presence of inflammation and hepatocyte injury.                                                                                                                                        &nb

Background: The healing process involves the restoration of the body’s structural integrity. The extracellular matrix, blood cells, cytokines, and growth factors are all involved in this dynamic, intricate, multicellular process. Hemostasis, the inflammatory phase, the proliferative phase, and the maturation phase are all included. Opuntia ficus-indica oil (OFI) and Punica grantum (PGS) oil are extensively used natural treatments that are regarded as advantageous for their sedative, spasmolytic, and anti-inflammatory properties, as well as for angiogenesis promotion, fibroblast increase, collagen production and deposition, and extracellular-matrix remodeling. Materials and methods: Twenty-four New Zealand rab

     This article aims to determine the time-dependent heat coefficient together with the temperature solution for a type of semi-linear time-fractional inverse source problem by applying a method based on the finite difference scheme and Tikhonov regularization. An unconditionally stable implicit finite difference scheme is used as a direct (forward) solver. While by the MATLAB routine lsqnonlin from the optimization toolbox, the inverse problem is reformulated as nonlinear least square minimization and solved efficiently. Since the problem is generally incorrect or ill-posed that means any error inclusion in the input data will produce a large error in the output data. Therefore, the Tikhonov regularization technique is applie